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Predictive Recommining: Learning Relations Between Event Log Characteristics and Machine Learning Approaches for Supporting Predictive Process Monitoring 1

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35th CAiSE Conference on Cyber-Human Systems

作者： Drodt, Christoph Weinzierl, Sven Matzner, Martin Delfmann, Patrick Univ Koblenz Inst Res Koblenz Germany Friedrich Alexander Univ Erlangen Nurnberg Inst Informat Syst Nurnberg Germany

ISBN: (数字)9783031346743

ISBN: (纸本)9783031346736;9783031346743

A variety of predictive process monitoring techniques based on machine learning (ML) have been proposed to improve the performance of operational processes. Existing techniques suggest different ML algorithms for training predictive models and are often optimized based on a small set of event logs. Consequently, practitioners face the challenge of finding an appropriate ML algorithm for a given event log. To overcome this challenge, this paper proposes Predictive Recommining, a framework for suggesting an ML algorithm and a sequence encoding technique for creating process predictions based on a new event log's characteristics (e.g., loops, number of traces, number of joins/splits). We show that our instantiated framework can create correct recommendations for the next activity prediction task.

关键词： Predictive Process Monitoring Machine Learning business Process Management Process Mining Decision Support

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Human-Computer Interaction: Ethical Perspectives on Technology and Its (Mis)uses 24th

Human-Computer Interaction: Ethical Perspectives on Technolo...

引用

24th International Conference on Enterprise information Systems (ICEIS)

作者： Cernat, Maria Bortun, Dumitru Matei, Corina Natl Sch Polit & Adm Studies Bucharest Romania Titu Maiorescu Univ Bucharest Romania

ISBN: (纸本)9783031393853;9783031393860

The developments in the human-computer interaction are astonishing. The Neuralink experiment showed a monkey literally moving a mouse on a computer screen "with its mind". The neuro device inserted in its brain was able to pick up the impulses and translate them into computer commands. Not very long ago, researchers presented an experiment in which a human patient diagnosed with severe depression had a neuro chip inserted in her brain to regulate her emotions. The fact that these major discoveries are not accompanied by equally well funded research to investigate the social, political and ethical implications that such results may have reveals the importance of this debate. The ethical challenges of human-computer interaction discoveries are themselves at the beginning since it is very difficult to keep up with the latest results. Nevertheless, it is vital that we start asking the important questions and put forward challenging hypotheses, since technology will not only be part = of our lives, abut also of our bodies.

关键词： Ethics Technology Human-computer interaction Deep brain stimulation

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Modern Warehouse and Delivery Object Monitoring - Safety, Precision, and Reliability in the Context of the Use the UWB Technology 19th

Modern Warehouse and Delivery Object Monitoring - Safety, Pr...

引用

19th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Hanzel, Krzysztof Silesian Tech Univ Dept Telecommun & Teleinformat Fac Automat Control Elect & Comp Sci Akad 16 PL-44100 Gliwice Poland

ISBN: (纸本)9783031306938;9783031306945

This document assesses six technologies - including visual or radio methods - currently used to monitor shipments and traffic in warehouses and logistics centers. The work presents eight important aspects from the point of view of systems monitoring the location of people and loads in areas where logistic operations are carried out. Among them, you can distinguish factors such as the accuracy of determining the distance aimed at improving the positioning of objects in warehouse spaces, the frequency of acquiring items that affect the safety and management of human resources, and the effectiveness of the system in unfavorable conditions in the form of objects on the line of sight. The document's conclusion indicates the preferential technology and the proposed application possibilities within industry 4.0. At the same time, the analysis showed that the existence of a universal method is currently impossible. Still, the dissemination of radio technologies such as UWB is a new opening in the aspect of warehouse management.

关键词： industry 4.0 warehouse management package tracking logistics

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Quantitative Comparison of Translation by Transformers-Based Neural Network Models 24th

Quantitative Comparison of Translation by Transformers-Based...

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24th International Conference on Enterprise information Systems (ICEIS)

作者： Smirnov, Alexander Teslya, Nikolay Shilov, Nikolay Frank, Diethard Minina, Elena Kovacs, Martin SPC RAS SPIIRAS 14th Line 39 St Petersburg Russia Festo SE & Co KG Ruiter Str 82 Esslingen Germany

ISBN: (纸本)9783031393853;9783031393860

One of the major tasks in producer-customer relations is a processing of customers' feedback. Since for the international companies provide their products for a lot of countries the feedback could be provided with various languages. That can produce a number of difficulties during automatic text processing. One of the solutions is to use one common language to process feedback and automatically translate feedbacks from the various languages to the common one. Then the translated feedback could be processed with the configured pipeline. This paper compares existing open models for automatic text translation. Only language models with Transformer architecture were considered due to the best results of translation over other existing approaches. The models are: M2M100, mBART, OPUS-MT (Helsinki NLP). Owntest datawas built due to requirement of translation for texts specific to the subject area. To create dataset Microsoft Azure Translation was chosen as the reference translation with manual translation verification for grammar. Translations produced by each model were compared with the reference translation using two metrics: BLEU and METEOR. The possibility of fast fine-tuning of models was also investigated to improve the quality of address the translation on specific lexicon of the problem area. Among the reviewed models, M2M100 turned out to be the best in terms of translation quality, but it is also the most difficult to fine-tune it.

关键词： Machine Translation DNN Translation Comparison Training Transformers Fine-Tuning

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Using Knowledge Graphs for Record Linkage: Challenges and Opportunities 1

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35th International Conference on Advanced information Systems Engineering (CAiSE)

作者： Andreou, Andreas S. Firmani, Donatella Mathew, Jerin George Mecella, Massimo Pingos, Michalis Cyprus Univ Technol Limassol Limassol Cyprus Sapienza Univ Roma Rome Italy

ISBN: (数字)9783031349850

ISBN: (纸本)9783031349843;9783031349850

In this paper, we explore how Knowledge Graphs (KGs) can potentially benefit Record Linkage (RL). RL is the process of identifying and resolving duplicate records across different data sources, including structured, semi-structured, and unstructured data (e.g., in data lakes). RL is a critical task for information systems that rely on data to make decisions and is used in a wide variety of fields such as healthcare, finance, government and marketing. Due to recent advances in machine learning, there has been a significant progress in building automated RL methods. However, when dealing with vertical applications, featuring specialized domains such as a particular hospital or industry, human experts are still required to enter domain-specific knowledge, making RL prohibitively expensive. Despite KGs can be powerful tools to represent and derive domain-specific knowledge, their application to RL has been overlooked. Inspired by a healthcare case study in the Republic of Cyprus, we aim at filling this gap by identifying challenges and opportunities of using KGs to reduce the effort of solving RL in vertical applications.

关键词： Health care

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TraVaS: Differentially Private Trace Variant Selection for Process Mining

TraVaS: Differentially Private Trace Variant Selection for P...

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4th International Conference on Process Mining (ICPM)

作者： Rafiei, Majid Wangelik, Frederik van der Aalst, Wil M. P. Rhein Westfal TH Aachen Chair Proc & Data Sci Aachen Germany

ISBN: (纸本)9783031278143;9783031278150

yIn the area of industrial process mining, privacy-preserving event data publication is becoming increasingly relevant. Consequently, the trade-off between high data utility and quantifiable privacy poses new challenges. State-of-the-art research mainly focuses on differentially private trace variant construction based on prefix expansion methods. However, these algorithms face several practical limitations such as high computational complexity, introducing fake variants, removing frequent variants, and a bounded variant length. In this paper, we introduce a new approach for direct differentially private trace variant release which uses anonymized partition selection strategies to overcome the aforementioned restraints. Experimental results on real-life event data show that our algorithm outperforms state-of-the-art methods in terms of both plain data utility and result utility preservation.

关键词： Process mining Differential privacy Event data

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Integrating Issue Management Systems of Independently Developed Software Components 24th

Integrating Issue Management Systems of Independently Develo...

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24th International Conference on Agile Software Development (XP)

作者： Speth, Sandro Breitenbuecher, Uwe Krieger, Niklas Wippermann, Pia Becker, Steffen Univ Stuttgart Inst Software Engn Stuttgart Germany Reutlingen Univ Herman Hollerith Zentrum Reutlingen Germany

ISBN: (纸本)9783031339752;9783031339769

Modern component-based architectural styles, e.g., microservices, enable developing the components independently from each other. However, this independence can result in problems when it comes to managing issues, such as bugs, as developer teams can freely choose their technology stacks, such as issue management systems (IMSs), e.g., Jira, GitHub, or Redmine. In the case of a microservice architecture, if an issue of a downstream microservice depends on an issue of an upstream microservice, this must be both identified and communicated, and the downstream service's issues should link to its causing issue. However, agile project management today requires efficient communication, which is why more and more teams are communicating through comments in the issues themselves. Unfortunately, IMSs are not integrated with each other, thus, semantically linking these issues is not supported, and identifying such issue dependencies from different IMSs is time-consuming and requires manual searching in multiple IMS technologies. This results in many context switches and prevents developers from being focused and getting things done. Therefore, in this paper, we present a concept for seamlessly integrating different IMS technologies into each other and providing a better architectural context. The concept is based on augmenting the websites of issue management systems through a browser extension. We validate the approach with a prototypical implementation for the Chrome browser. For evaluation, we conducted expert interviews, which approved that the presented approach provides significant advantages for managing issues of agile microservice architectures.

关键词： Microservices Issue management Service engineering Component-based architectures Gropius Browser extension

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Genetic Algorithms for AutoML in Process Predictive Monitoring

Genetic Algorithms for AutoML in Process Predictive Monitori...

引用

4th International Conference on Process Mining (ICPM)

作者： Kwon, Nahyun Comuzzi, Marco Ulsan Natl Inst Sci & Technol Ulsan South Korea

ISBN: (纸本)9783031278143;9783031278150

In recent years, AutoML has emerged as a promising technique for reducing computational and time cost by automating the development of machine learning models. Existing AutoML tools cannot be applied directly to process predictive monitoring (PPM), because they do not support several configuration parameters that are PPM-specific, such as trace bucketing or encoding. In other words, they are only specialized in finding the best configuration of machine learning model hyperparameters. In this paper, we present a simple yet extensible framework for AutoML in PPM. The framework uses genetic algorithms to explore a configuration space containing both PPM-specific parameters and the traditional machine learning model hyperparameters. We design four different types of experiments to verify the effectiveness of the proposed approach, comparing its performance in respect of random search of the configuration space, using two publicly available event logs. The results demonstrate that the proposed approach outperforms consistently the random search.

关键词： AutoML Genetic algorithm Predictive process monitoring Hyperparameter optimization

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Can Process Mining Detect Video Game Addiction Through Player's Character Class Behavior? 19th

Can Process Mining Detect Video Game Addiction Through Playe...

引用

19th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Guenego, Maxime Deneckere, Rebecca Univ Paris 1 Pantheon Sorbonne Ctr Rech Informat Paris France

ISBN: (纸本)9783031306938;9783031306945

For more than fifteen years, we have witnessed the effervescence of video games, first considered by a handful of scholars this hobby knew how to penetrate most homes. Video games are no longer necessarily considered a simple hobby, players have been able to take advantage of this enthusiasm to make a business, the birth of e-sport, community channels, and various monetized videos are proof of this. However, the news shows us that for some people video games can become a real addiction and bring with it its share of the problem. Since video games are by nature computer programs, we may wonder if it is not possible to retrieve information about their users in real-time to detect any addictive behavior and thus protect the player. In this paper, we will use process mining techniques to analyze player logs to try to find a behavioral pattern of addiction.

关键词： Addiction Video Games Process Mining

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Enhancing Data-Awareness of Object-Centric Event Logs

Enhancing Data-Awareness of Object-Centric Event Logs

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4th International Conference on Process Mining (ICPM)

作者： Goossens, Alexandre De Smedt, Johannes Vanthienen, Jan van der Aalst, Wil M. P. Katholieke Univ Leuven Leuven Inst Res Informat Syst LIRIS Leuven Belgium Rhein Westfal TH Aachen Proc & Data Sci PADS Chair Aachen Germany

ISBN: (纸本)9783031278143;9783031278150

When multiple objects are involved in a process, there is an opportunity for processes to be discovered from different angles with new information that previously might not have been analyzed from a single object point of view. This does require that all the information of event/object attributes and their values are stored within logs including attributes that have a list of values or attributes with values that change over time. It also requires that attributes can unambiguously be linked to an object, an event or both. As such, object-centric event logs are an interesting development in process mining as they support the presence of multiple types of objects. First, this paper shows that the current object-centric event log formats do not support the aforementioned aspects to their full potential since the possibility to support dynamic object attributes (attributes with changing values) is not supported by existing formats. Next, this paper introduces a novel enriched object-centric event log format tackling the aforementioned issues alongside an algorithm that automatically translates XES logs to this Data-aware OCEL (DOCEL) format.

关键词： Object-centric event logs Process mining Decision mining

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